---
title: vlite
---

This page covers how to use [vlite](https://github.com/sdan/vlite) within LangChain. vlite is a simple and fast vector database for storing and retrieving embeddings.

## Installation and Setup

To install vlite, run the following command:

<CodeGroup>
```bash pip
pip install vlite
```

```bash uv
uv add vlite
```
</CodeGroup>

For PDF OCR support, install the `vlite[ocr]` extra:

<CodeGroup>
```bash pip
pip install vlite[ocr]
```

```bash uv
uv add vlite[ocr]
```
</CodeGroup>

## VectorStore

vlite provides a wrapper around its vector database, allowing you to use it as a vectorstore for semantic search and example selection.

To import the vlite vectorstore:

```python
from langchain_community.vectorstores import vlite
```

### Usage

For a more detailed walkthrough of the vlite wrapper, see [this notebook](/oss/integrations/vectorstores/vlite).
